Senior Director - Engineering

<p><strong>Responsibilities:</strong></p><p>We are looking for a visionary technology leader to take the charge of our AI Analytics group, a leader who makes bold moves and inspires their teams to set high standards for craftsmanship, resilience, and scale.</p><p>As the Senior Director of Engineering for AI Analytics, you will be empowered to make an impact by owning the strategic vision and technical execution for all core services. You will lead a world-class organization of engineers and managers, fostering a culture of innovation and collaboration where we win as one team. This is a pivotal role with the opportunity to influence our entire product portfolio and deliver the speed and reliability our customers depend on.</p><p><strong>Key responsibilities</strong></p><ul><li>Lead a multi-disciplinary org: analytics engineers, BI developers, and data product leaders.</li><li>Build scalable pipelines and data products (bronze/silver/gold patterns), ensuring data quality, lineage, and reliability.</li><li>Establish governance: access controls, data classification, privacy/PII handling, audits, and compliance-ready practices.</li><li>Drive an insights product mindset: stakeholder discovery, prioritization, MVPs, adoption measurement, iteration.</li><li>Deliver executive-ready narratives and business reviews: concise insights, drivers, recommendations, and clear next steps.</li><li>Define and track impact: adoption, decision velocity, deflection, productivity gains, risk reduction, and ROI.</li><li>Work with the Data Science team on creating state of the art models.</li></ul><p><strong>What You'll Do (Responsibilities)</strong></p><ul><li><strong>Set the Analytics &amp; Insights vision</strong>: Define the strategy, roadmap, and operating model to deliver reliable, outcome-focused insights across Product, Support, Sales, Marketing, Finance, and Operations.</li><li><strong>Build proactive intelligence</strong>: Ship systems that detect anomalies, forecast risk, and surface emerging trends—pushing insights to stakeholders proactively (not waiting for dashboards).</li><li><strong>Deliver agentic insights</strong>: Partner with AI/ML and product teams to build AI assistants/agents (e.g., an “Insights Copilot”) that answer questions, generate narratives, recommend next-best actions, and integrate into the tools teams already use.</li><li><strong>Own the modern data + insights platform</strong>: Lead the end-to-end analytics ecosystem on <strong>Databricks (Lakehouse)</strong>—including orchestration, governance, semantic layer, and BI—to maximize speed, trust, and scalability.</li><li><strong>Establish a single source of truth</strong>: Standardize KPI definitions and metric governance, ensuring consistent reporting and decision-making across teams.</li><li><strong>Scale self-serve analytics</strong>: Drive adoption through curated data products, templates, enablement programs, and strong stakeholder partnerships that reduce ad-hoc asks and increase autonomy.</li><li><strong>Close the insights-to-action loop</strong>: Build processes and tooling so insights translate into decisions and measurable impact (cost reduction, retention lift, improved SLA performance, faster resolution, revenue acceleration).</li><li><strong>Lead &amp; Inspire: </strong>Cultivate a high-performance, inclusive culture across a multi-tiered organization of engineers and managers. Mentor the next generation of technical leaders and build a world-class team that is known for its technical excellence and execution velocity.</li><li><strong>Execute with Excellence: </strong>Master the entire development lifecycle, from strategic planning and roadmap management to deployment and operations. Champion agile and iterative development methodologies to ship exceptional products under ambitious deadlines and evolving business priorities.</li><li><strong>Drive Technical &amp; Architectural Strategy: </strong>Act as the ultimate technical authority for the platform. Guide ... (truncated, view full listing at source)